Characterizing the Fire Threat to Wildland Urban Interface Areas in California

Transcription

1 Introduction Characterizing the Fire Threat to Wildland Urban Interface Areas in California This document outlines the procedures used to identify areas in California that pose significant threats from wildfire to the people of California. It was prepared under the auspices of the California Fire Alliance -- a coalition of representatives from State and Federal Fire Agencies, originally formed in 1996, who have collaborated on integrating fire management and planning across jurisdictional boundaries. While much of the basic premise and data for the development of this analysis has a beginning in the California Department of Forestry and Fire Protection s California Fire Plan, this work represents new and original work that is sanctioned by the USDA Forest Service, the USDI Bureau of Land Management and National Park Service, in addition to CDF. The Fire Alliance views the issue of the wildland interface as a natural area for collaboration, and is optimistic that the following analysis can be a model for other areas. The analysis was prepared in response to a mandate from Congress in the Interior Appropriations bill establishing the National Fire Plan. Utilizing a Geographic Information System (GIS) approach that is at the heart of the California Fire Plan, the three main components in the assessment of threat from wildland fire to Wildland-Urban Interface areas of California are: Ranking fuel hazard Assessing the probability of wildland fire Defining areas of suitable housing density that lead to Wildland-Urban Interface fire protection strategy situations These three independent components were then combined using GIS capabilities to identify wildland interface areas threatened by wildfire. In addition to mapping these areas, a list of communities was developed that summarized a non-spatial assessment of key areas within the vicinity of significant threat from wildland fire. A subset of that list was made that includes those communities that have a significant fire threat from nearby Federal lands. A buffer distance of 1.5 miles was used in the analysis to define nearby federal lands. 1

2 Methods 1. Defining Fuel Hazard The California Department of Forestry and Fire Protection s Fire and Resource Assessment Program staff built a methodology of assigning fire hazard across diverse landscapes of California as part of California s Fire Plan. The first step in the hazard assessment process is development of a vegetation map based on the best available, most recent and detailed vegetation composition and structure information. These vegetation maps were then translated (using a crosswalk process similar to that used in the Sierra Nevada Ecosystem Project but specific to each local area) to Fire Behavior Prediction System (FBPS) fuel models. Recent large fires are mapped and used to change the base map to better reflect current wildland fuel conditions. A forest growth model is included to account for new vegetation growth since the last wildfire. The California Interagency Fuel Mapping Group guided this assessment and resolved mapping differences at jurisdictional boundaries, producing a seamless map of fuel characteristics across all ownerships and protection jurisdictions. That is, local representatives of Federal, State and local fire agencies have contributed to the development of the statewide fuels data. The next step in this assessment is to convert the fuels map to a fire hazard map. Potential fire behavior drives the hazard ranking with fire hazard defined as the fire behavior potential of the wildland fuel, given average bad fire weather conditions. Fire behavior is calculated using the Fire Behavior Prediction System equations and then summarized into moderate, high, or very high classes. The method first calculates the expected fire behavior for unique combinations of slope and fuels under average bad fire weather conditions. Figure 1 portrays the rate of spread and heat flux of the fuel-byslope-class combinations on top of three fireline intensity iso-curves that divide the space into hazard rank subspaces. Thus, each fuel-by-slope-class combination receives a surface hazard rank according to its location within Figure 1. 2

3 Figure 1. Fire behavior characteristics chart of fuel models by NFDRS slope classes. 600 Fire Behavior Characteristics Rate of Spread ' 200 Very High 8' 100 4' High Moderate Heat per Unit Area In this graph, each column of x s represents the fire behavior characteristics of a fuel type burning on increasingly steep slopes. The area above and to the right of the blue line indicates fire behavior with flame lengths greater than 11 feet in the surface fuels. The area between the green line and the blue line indicates fire behavior with flame length potential between 8 feet and 11 feet. The red line is the 4-foot flame length line. Surface hazard is moderate for fuel types in the 0 4 foot flame length area, high for the 4 8 foot flame length area and very high for fuels with greater than 8 foot flame length potential. The Fire Plan process uses a grid system for data analysis. Staff formed the grid by partitioning each 7.5 USGS quadrangle sheet into 81 (9-by-9) miniquads. Each grid cell is approximately 450 acres. This method allows more complex data to be summarized and presented in a consistent mapping process. A surface fire hazard map is made by assigning a hazard ranking to each grid cell based on its slope class and fuel model. The final fire hazard includes an assessment of 2 additional factors that lead to severe fire behavior (ladder and crown fuels). Figure 2 shows the spatial allocation of fuel hazards across California as developed through this methodology. 3

4 Figure 2 shows the spatial allocation of fuel hazards across California 4

5 2. Probability of Burning The probability of a fire burning in a given location is based on a milieu of factors including vegetative fuel condition, weather, ignition source, fire suppression response, and more. The Fire and Resource Assessment Program staff has analyzed 47 years of fire history from with respect to vegetation type, bio-region, and owner class to produce a 3 class ranking of the probability of a costly damaging fire (PFIRE). The method used to determine PFIRE was similar to the calculation of fire rotation used in analyzing fire regimes. Fire perimeter data (from all of the wildland fire protection agencies) was overlaid on the vegetation type map to determine how many acres burned in each vegetation type during the entire period of record. These values were then divided by the total area in that particular vegetation type multiplied by the number of years of fire perimeter data in the record. The calculated probability values are then grouped into the following three classes: Very High (probability of a fire is 1% per year or greater) High (probability of a fire is 0.33% - 1% per year) Moderate (probability of a fire is less than 0.33% per year) These values are equivalent to fire frequencies of less than 100 years, years, and greater than 300 years, respectively. The resultant figure represents the annual likelihood that a large damaging wildfire would occur in that particular vegetation type. The analysis is summarized by watershed and ranked based on the highest PFIRE identified through this analysis. Figure 3 shows the distribution of PFIRE within California. 5

6 Figure 3 identifies the probability of a given piece of ground burning 6

7 3. Defining the Urban-Interface Areas of concern regarding housing and public safety were defined as those areas that have a structure density of 1 house per 40 acres, or denser, as calculated from the 1990 census block data. The census data is resolved into polygons called blocks, designed to hold roughly 400 people, and consequently vary widely in size and shape depending on the nature of development in a given area. Often, census blocks include many areas that are not typically developed, so the density of housing is not accurately represented by dividing the number of houses by the acres in the census block. To resolve this problem, staff migrated the density from areas of restricted development to areas of non-restricted development. Federal land is considered restricted development land in this analysis (houses in the wildland are on private ownership rather than federal ownership, generally). The migrated census data is categorized based on density and grouped into the following classes: Urban (more than one house per 0.5 acres) Intermix (from one house per 0.5 acres to one house per 5 acres) Rural (from one house per 5 acres to one house per 40 acres) Wildland (less than one house per 40 acres). Figure 4 shows the breakdown of these areas for the entire State. 7

8 Figure 4 characterizes the extent and density of the Wildland-Urban Interface. 8

9 4. Assessing Fire Threat Staff calculated a numerical index of fire threat based on the combination of hazard rank and fire probability. A 1 3 ranking from PFIRE (probability of a damaging fire occurring) was summed with the 1 3 ranking from the fuel hazard component to develop a threat index ranging from 2 to 6. This threat index is then grouped into three threat classes. Scores from four to six received a high threat rank; a score of three received a moderate threat rank; and a score of two received a low threat rank (Table 1). Areas that did not support wildland fuels (e.g., open water, agriculture lands, etc.,) were omitted from the calculation of fire threat (Figure 5). Additionally, areas of very large urban centers (i.e., concrete jungles ) were also removed from the final analysis by combining the fire threat coverage with the urban-interface coverage. Table 1. Fire threat matrix based on hazard rank and fire probability. Hazard Rank PFIRE 1 (Moderate) 2 (High) 3 (Very High) 1 (Moderate) 2 (Low) 3 (Moderate) 4 (High) 2 (High) 3 (Moderate) 4 (High) 5 (High) 3 (Very High) 4 (High) 5 (High) 6 (High) 9

10 1) Figure 5 shows California s Fire Threat Zones 10

11 5. Identifying Fire Threatened Wildland-Interface Areas The final step in the analysis was to search for all areas identified in the urban- interface layer that were in the vicinity of fire threats. Staff defined vicinity as all areas within 1.5 miles of a fire threat. Consequently, all areas with WUI values from 1 to 3 (i.e., densities greater than one house per 40 acres except those not supporting wildland fuels or in large urban centers) were labeled with the highest threat rank within a 1.5 mile radius. A 0.25 mile high density buffer for the urbanized density class (i.e., greater than 1 house per 0.5 acre) was included to account for the peripheral areas of urban centers abutting wildlands. Hence, high density areas lying immediately adjacent to wildlands would be included, but not those urbanized areas in the central parts of cities. The resultant map of threatened Wildland- Interface areas shows not only the aerial extent of affected areas, but also the relative fire threat to those areas (Figure 6). 11

12 Figure 6 shows fire threatened areas in the Wildland-Urban interface 12

13 6. Threatened communities As a final product, the data in Figure 6 was overlaid on a map of place names to derive a list of communities threatened by wildfire. Place names (from the U.S. Census Bureau) can be selected based on the level of threat posed to them. A similar subset list can be made to find those threatened communities that are within the vicinity of federal ownership. For mapping purposes, a 1.5 mile buffer distance or other appropriate buffer distance can be used to define vicinity. To accomplish this, a mask of the fire threat data can be created to highlight only those areas on Federal lands, and then run the same calculations performed statewide. The list of these place names, and corresponding fire threat level is given in Appendix A, List of Fire Threatened Communities in California. The list separates those communities having some or all of their fire threat coming from federal lands from those where none of their fire threat comes from federal lands. Discussion While we believe the analysis presented accurately defines WUI areas potentially under threat from wildland fire, a number of caveats to the analysis are warranted. First, we have based our assessment based on the proximity of houses and fire threat as defined by hazard and fire probability. Additional data, such as fire weather frequency, may improve the development of the fire threat construct. However, in as much as solutions to the WUI issue largely focus on mitigating hazard and improving structure and surroundings characteristics to avoid house ignition, we feel that this scheme of density of housing and assessments of wildland fire threats should form the key components of an effective analytical framework for addressing the problem. One key element that has emerged in other assessments directed at this and similar land management issues, is the use of other resource data that might be combined into the framework. As an example, if watersheds providing municipal water supplies were viewed as important in selecting wildland areas for mitigation of fire threats, where both watershed and community protection objectives might be realized, GIS-based data on watersheds could be brought into the analysis. In fact, this is the very foundation of the California Fire Plan. Managing for wildfire is a complex business, and there is no reason to believe that we should arbitrarily limit the complexity of our planning tools. However, we are also obliged to note that constraints and caveats to the underlying data classifications, resolution, and accuracy could call into question the derived assessment when looked at under a microscope. If additional data is included, it simply also brings to bear these same issues as they relate to these new data. For the purposed of broadly defining these areas at the Statewide scale, we are confident that the data used here are sufficient to the task. We further believe that errors in our assessment would be selected out during the 13

14 project level planning process where refinement of project planning required to mitigate fire threats to people is undertaken. As the Fire Alliance has supported refinement of existing data, and the development of new data, we think that this assessment approach can easily incorporate new information as it becomes available. We also believe it is sufficiently flexible such that the framework can change to take advantage of new ideas in characterizing and classifying the Wildland-Urban Interface issue. Disclaimers This mapping analysis will need field review to validate the basic assessments and conclusions. The California Fire Plan process calls for using the best available data for analysis and having field fire managers and community stakeholders validate the underlying data. Tactical project decisions are then made on the best combination of strategic assessments and local knowledge. Most of the data sets used in this analysis have gone through this field validation process. However, several data sets are taken as is and may not reflect actual current conditions. The urban-wildland interface assessment and the community names list are based on 1990 Census Bureau information. There is a good likelihood that communities have been omitted that should be included and there are probably communities included that should be omitted. California is experiencing rapid growth, especially in rural areas removed from the urban centers. Validating and updating the basic 1990 census data is beyond the capability of field managers and stakeholders so existing data is used as is with the intent of updating the analysis when the 2000 census data is available. One basic assumption in the Wildland-Urban Interface housing density mapping is that the houses in a census block are on the private land portion of the block and not on the federal land. There may be local exceptions to this assumption, for example: concentrations of summer cabins on national forest leases. Also, we assumed housing is evenly distributed over the private land portion of the census block. Field validation may find concentrations of housing that could alter the housing density mapping. The hazard assessment is based on the best available vegetation maps. In some parts of California this data is very good. However, in other areas the vegetation mapping is old and otherwise less than desirable. Field validation has corrected many mapping errors but probably not all. The fire probability assessment includes fire perimeter maps for all agencies dating back to Older fire perimeters were digitized from paper map archives. The maps have been field validated to the extent that this history is available. It is possible that some fires are not in the database. This mapping is a cooperative effort between local and state wildland fire agencies and federal 14

15 land management agencies with wildland fire protection responsibilities. The possibility exists that some fires from other land managers have not yet been included. For example, fires on military bases and prescribed fires on private ownerships may be missing from this analysis. Field validation efforts are focused on areas of greatest concern, areas where their efforts will have the greatest impact. In other words, community stakeholders and fire managers are not spending a lot of time fine-tuning data in areas where they know fires are not a problem. The benefit to this approach is that projects are being proposed and developed in the most important areas. The caution is for those making decisions removed from this local knowledge base; the base data may not be perfect. 15